Statistics Question

[lakay0309]

The median of any normal distribution is the same as its mean. We can find the quartiles for any distribution, even in a normal distribution (a symmetric distribution). The following questions will lead yu through finding the quartiles in a normal distribution.

a. what percentage of values under the standard normal curve are smaller than the first quartiles?

b. what percentage of values under the standard normal curve are smaller than the third quartiles?

c. using the information from parts (a) and (b) as well as what you know about normal distributions, find the value of the first quartile and third quartile for any standard normal distribution.

d. what is the IQR for the standard normal distribution

e. Police response time to an emergency call is the time difference between the time the call is first received by the dispatcher and the time a patrol car radios tht it has arrived at the scene. Over a long period of time it has been determined that the police response time has a normal distribution with mean 8.4 minutes and standard deviation 1.7 minutes. Find the quartiles of the response times.


((if i could get as much help as possible, i'm completely lost
thanks))

 

[wjm11]

The median of any normal distribution is the same as its mean. We can find the quartiles for any distribution, even in a normal distribution (a symmetric distribution). The following questions will lead yu through finding the quartiles in a normal distribution.

a. what percentage of values under the standard normal curve are smaller than the first quartiles?

In your book, you should find a Table A -- Standard Normal Probabilities. All you have to do is read from this table. The "z" scores are the number of standard deviations away from the mean.

Example: Look in the table and find a number close to .25 (representing 25%). The closest number is .2514 . It is in the column under ".07" and in the row that has a z-score of -.6 . This means that about 25% of the area under the curve lies to the left of the point defined by -.67 standard deviations.